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Commentary: What you need to know about AI’s role in your A&E visit

SINGAPORE: Imagine this scenario: You’re in a crowded emergency room in one of Singapore’s hospitals. Around you, dozens of patients are waiting to be triaged and seen by a doctor. The flow of incoming patients is constant: Some arrive by ambulance, their conditions appearing critical and dire, while others, with more minor complaints, wait to be seen in the waiting room.

In the midst of this, a triage scoring tool built upon an AI model specifically for use in the emergency department works behind the scenes, helping medical staff decide which patients should be seen first.

The doctor in charge of the triage process makes a professional judgment about how quickly the patient should be seen and what treatment should be instigated, and then consults the AI-produced triage score to consider whether it would be appropriate to modify their plan in any way. Here, the AI model is “in the loop” of human decision-making, but it is the doctor who is calling the shots. The AI model is simply supporting the doctor’s professional judgment.

Consider a second, slightly modified scenario where the doctor is mere technician, putting in place a triaging plan entirely based on the score produced by the AI model, free from any professional judgment.

Which of these two approaches is to be preferred will, in part, depend on how effective the AI triage scoring tool is compared to the judgment of expert clinicians. But both approaches also raise a further question: Do patients have the right to know the role the AI model is playing in critical decisions about how long they must wait to see a doctor?

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